TY - JOUR
T1 - Realization of future neuro-biological architecture in power efficient memristors of Fe3O4/WS2 hybrid nanocomposites
AU - Ghafoor, Faisal
AU - Ismail, Muhammad
AU - Kim, Honggyun
AU - Ali, Muhammad
AU - Rehman, Shania
AU - Ghafoor, Bilal
AU - Khan, Muhammad Asghar
AU - Patil, Harshada
AU - Kim, Sungjun
AU - Khan, Muhammad Farooq
AU - Kim, Deok kee
N1 - Publisher Copyright:
© 2024
PY - 2024/4
Y1 - 2024/4
N2 - The future generation of digital technology will heavily rely on power efficient non-volatile resistive memory systems as a potential alternative to flash memory due to its limitations in scalability and endurance. To attain the commercial benchmark, memristors have still lacked performance. This study reports a novel and cost-effective solution processable method for growing surface-modified hybrid nanocomposites (Nc) on a large scale, as an active layer. The solution-processed synthesis approach used for Ag/Fe50W50/Pt hybrid nanocomposite memristor device results in the formation of heterophase grain boundaries, which create residual filaments along these boundaries. The device Fe3O4-WS2(Nc) shows excellent performance, having ultra-low energy consumption (0.1fJ), high reproducibility (10 devices), scalability, excellent endurance (106), and excellent environment stability. Density functional theory (DFT) simulations reveal that structural symmetry distortion and interfacial interaction of hybrid nanocomposite at the interface plays a vital role in the switching mechanism. As high-performance electronic synapses, the optimal pulse scheme enables a steady interaction of short- and long-term plasticity principles, such as spike -time dependent plasticity (STDP) and pulse pair facilitation (PPF), essential for learning and neuromorphic computing analogous to human brain. Moreover, by using Modified National Institute of Standards and Technology (MINST), the memristor device attained a high learning accuracy of 95.4% under convolution neural network (CNN) simulations. The present study revealed that the performance of hybrid-nanocomposite memristors could lead to efficient future neuromorphic architecture.
AB - The future generation of digital technology will heavily rely on power efficient non-volatile resistive memory systems as a potential alternative to flash memory due to its limitations in scalability and endurance. To attain the commercial benchmark, memristors have still lacked performance. This study reports a novel and cost-effective solution processable method for growing surface-modified hybrid nanocomposites (Nc) on a large scale, as an active layer. The solution-processed synthesis approach used for Ag/Fe50W50/Pt hybrid nanocomposite memristor device results in the formation of heterophase grain boundaries, which create residual filaments along these boundaries. The device Fe3O4-WS2(Nc) shows excellent performance, having ultra-low energy consumption (0.1fJ), high reproducibility (10 devices), scalability, excellent endurance (106), and excellent environment stability. Density functional theory (DFT) simulations reveal that structural symmetry distortion and interfacial interaction of hybrid nanocomposite at the interface plays a vital role in the switching mechanism. As high-performance electronic synapses, the optimal pulse scheme enables a steady interaction of short- and long-term plasticity principles, such as spike -time dependent plasticity (STDP) and pulse pair facilitation (PPF), essential for learning and neuromorphic computing analogous to human brain. Moreover, by using Modified National Institute of Standards and Technology (MINST), the memristor device attained a high learning accuracy of 95.4% under convolution neural network (CNN) simulations. The present study revealed that the performance of hybrid-nanocomposite memristors could lead to efficient future neuromorphic architecture.
KW - Heterophase Grain Boundaries (GB)
KW - Hybrid Nanocomposite (Nc)
KW - Iron Oxide (FeO)
KW - Neuromorphic computing
KW - Tungsten disulphide (WS)
UR - http://www.scopus.com/inward/record.url?scp=85182870236&partnerID=8YFLogxK
U2 - 10.1016/j.nanoen.2024.109272
DO - 10.1016/j.nanoen.2024.109272
M3 - Article
AN - SCOPUS:85182870236
SN - 2211-2855
VL - 122
JO - Nano Energy
JF - Nano Energy
M1 - 109272
ER -